code: def main(argv):
      data_path = os.path.join(
          FLAGS.datadir, "training-monolingual.tokenized.shuffled/*"
      )
  
      train_dataset = gen_lm1b_train_dataset(data_path, FLAGS.num_steps)
      train_dataset = train_dataset.batch(FLAGS.batch_size)
      model = language_model.LM(FLAGS.num_steps)
      prev_time = time.time()
      for local_step, input_data in enumerate(train_dataset.take(10)):
          loss, _ = model.train_step(input_data)
          if local_step % FLAGS.log_frequency == 0:
              cur_time = time.time()
              elapsed_time = cur_time - prev_time
              num_words = FLAGS.batch_size * FLAGS.log_frequency
              wps = float(num_words) / elapsed_time
              logging.info(
                  "Iteration %d, time = %.2fs, wps = %.0f, train loss = %.4f"
                  % (local_step, cur_time - prev_time, wps, loss)
              )
              prev_time = cur_time
  
file_path: autodist/examples/lm1b/lm1b_train_eager.py
imports: import os
  import time
  import json
  import glob
  from absl import app
  from absl import flags
  from absl import logging
  import tensorflow
  import language_model
label_desc: Use image node_id 2 for calling a global function with example usage: main(argv) without return types